Geschäftsführung und Koordination

Rea Kodalle

S 1-130

+49 (0)441 798-5481


Prof. Dr. Gisela Schulze

A01 1-132

+49 (0)441 798-2175

Koordination des Programms 'Schreibbegleitung'/Evaluation

Robert Mitschke

Wissenschaftliche Hilfskräfte

Alischa Marquart und Jan Gruß



Understanding & Applying Binary Logistic Regression with Stata

3GO-Workshop 3GO + OLTECH 3GO + Graduiertenakademie 3GO + Kulturen der Partizipation

---Achtung--- Dieser Workshop wird in den Herbst verschoben!


Speaker: Dr. rer. pol. Berna Öney

Logistic Regression is a great tool for attributing cause-effect relationships where the response is a categorical variable. Many courses/workshops on statistical methods only briefly cover the interpretation of the logistic regression results; however, interpreting logistic regression results go beyond examining coefficients and standard errors as in OLS regression models. This workshop will provide researchers necessary means to understand and present the logistic regression results in the most effective way possible.

The focus throughout the course will not only be placed on theoretical logic but also on the practical analysis. By the end of the workshop, participants will be able to: (1) interpret the results using log odds, odds ratios, and predicted probabilities; (2) present the results as tables and graphs; (3) interpret interaction effects properly; (4) apply various measures of model fit; (5) run diagnostic tests; and (6) use Stata to run binary logistic regression models.

For each step mentioned above, after theoretical discussions, there will be a practical application part. Participants will get the STATA commands from the instructor and apply the code to the given examples. Besides this in-class exercises, participants are encouraged to bring their data and research questions.

This course is at an advanced level, so some familiarity with OLS regression as well as with the basics of logistic regression will be assumed. As a mainly hands-on, practical course, basic knowledge of Stata is required.

Participants restriction: 16

Registration: Stud.IP.


29. Juni 2018 – 30. Juni 2018

(Stand: 23.10.2020)